detect-freight-led-inflation-turn

Detect inflation turning points by analyzing CASS Freight Index YoY cycles and CPI lead-lag relationships. This Skill monitors Shipments YoY and Expenditures YoY to identify cycle peaks and valleys, determining whether inflation is easing for macro research.

The CASS Freight Index leads CPI because shipping costs and freight expenditures signal supply chain price pressures before consumer prices reflect them. This Skill assesses the lead-lag relationship between CASS YoY and CPI to gauge inflation trend direction.

Scrape CASS Freight Index data from MacroMicro using Chrome remote debugging and Selenium. Start Chrome with a remote debugging port 9222, open the MacroMicro chart URL, and run the fetch_cass_freight.py script with the --cdp flag to capture structured time-series data.

You can use pandas and numpy for freight-cycle turning detection without Selenium if you supply cached freight data. Selenium is optionally required only for automated data capture from MacroMicro; running the detector script with existing data requires just requests, pandas, and numpy.

You need requests, websocket-client, pandas, and numpy for freight inflation detection. Optionally, install selenium and webdriver-manager if you require automated Chrome CDP data capture from MacroMicro charts rather than using cached or manually downloaded freight index data.

Run a quick freight inflation check using the --quick flag for immediate signal generation. For full historical analysis, use the --start parameter with a date like 2015-01-01 and --lead-months to define the CPI lead-lag window, producing detailed visualizations and structured turning point signals.