What problem does it solve?
This Skill addresses the complexities of ETF arbitrage by providing structured workflows for research, implementation, and production controls, focusing on primary-secondary dislocations, basket liquidity, and creation-redemption frictions.
Core Features & Use Cases
- Reproducible Research: Ensures that ETF arbitrage strategies are developed with clear hypotheses, leak-safe features, and robust estimation of signal edge and capacity.
- Production Controls: Implements stress testing across various market regimes and enforces risk controls like exposure ceilings and deactivation triggers.
- Use Case: When dealing with discrepancies between an ETF's market price and its net asset value, this Skill helps in identifying, analyzing, and executing arbitrage opportunities while managing associated risks.
Quick Start
Run python scripts/etf_arbitrage_diagnostics.py input.csv --output diagnostics.json to generate diagnostics for ETF arbitrage.