analyze-platinum-to-brazil-equities-transmission

You can analyze the platinum to EWZ transmission using public market data to identify long-cycle lead-lag structures, tracking rolling correlation stability and classifying market regimes to quantify whether platinum futures lead or co-move with the Brazil ETF.

Rolling correlation stability tracks the time-varying association between platinum and EWZ to assess whether the transmission relationship holds consistently over time or breaks down under different market conditions.

Yes, you can classify market regimes for platinum and EWZ using public Yahoo Finance data. The framework categorizes the current market environment into linked_upcycle, decoupled, or brazil_idiosyncratic regimes to contextualize the transmission analysis results.

You generate a Bloomberg-style chart for platinum to EWZ monitoring by running the full analysis with default weekly frequency, which outputs the visualization alongside JSON and Markdown reports to track the transmission relationship.

Yes, you need numpy and pandas as dependencies to run the platinum to EWZ transmission analysis. These libraries handle the data manipulation and mathematical calculations required for the rolling correlation and lead-lag structure computations.

Regime classification for ETF transmission analysis relies on historical public market data, meaning it may not capture sudden structural breaks or real-time macroeconomic shifts. The framework classifies regimes like decoupled or brazil_idiosyncratic to contextualize but not predict the platinum to EWZ relationship.