correlation-analysis

To find cointegrated pairs for pairs trading, analyze return time series to expose high-correlation and cointegration signals, running Engle-Granger and Johansen rank tests to validate long-run equilibrium before committing capital.

A Kalman hedge ratio is a dynamic measure of the relative weighting between two assets in a spread, calculated by applying a Kalman filter to return time series to derive adaptive hedging parameters for robust pair-trading execution.

Yes, you can use correlation analysis for sector clustering across a multi-asset universe, applying co-movement discovery and realized correlation monitoring to group assets and track cross-market linkage dynamics.

The best way to generate Z-score thresholds for a mean-reversion strategy is to compute the half-life of mean reversion and derive signal thresholds from the spread's historical distribution, ensuring quantitative validation before execution.

Conditional correlations adjust for bull, bear, and high-volatility regimes by tracking realized correlation studies across different market environments, allowing you to monitor how asset linkages evolve and adapt to shifting volatility.

You should adjust for FX impacts on cross-market correlation spreads when analyzing international asset universes, ensuring that realized correlation studies reflect true underlying co-movements rather than currency-driven distortions.