monitor-etf-holdings-drawdown-risk

You can detect ETF price-to-holdings divergence by running the divergence detector script with yfinance price data and holdings data, which computes divergence and stress scores to flag potential physical tightness and delivery risk.

Physical tightness signals include price-to-holdings divergence, inventory trends hitting decade-lows, futures curve structure changes, and elevated retail premia, all cross-validated through multi-indicator checks within the data pipeline.

Yes, the Skill cross-validates potential delivery risk by checking inventory trends, decade-low analysis, futures curve structure, and retail premia alongside the primary ETF price-to-holdings divergence signal.

Run the divergence detector script with the --quick flag, specifying the ETF ticker and commodity futures symbol, to fetch prices and holdings data and output a structured divergence status result.

Yes, the Skill uses Selenium, webdriver-manager, and beautifulsoup4 alongside pandas, numpy, and yfinance to fetch holdings data, commodity prices, and retail premia for cross-validation of divergence signals.

Divergence detection relies on accurate holdings data and multiple cross-checks; signals may lag during rapid market dislocations, and retail premia scraping can break if source websites change their structure.