correlation-analysis

You can calculate rolling correlation between financial assets to track how relationships change over time for risk management. This Skill computes Pearson, Spearman, and Kendall correlations alongside EWMA to quantify inter-asset dynamics across various timeframes.

Hierarchical clustering groups similar assets to identify portfolio diversification opportunities. By analyzing cross-asset correlation matrices, you can uncover hidden asset relationships and avoid concentrated risks within your financial portfolios.

Tail dependence estimation assesses how assets move together during extreme market events like crashes. By quantifying these tail dependencies, you can identify hidden systemic risks in your portfolio that standard correlation metrics might miss during financial downturns.

Eigenvalue decomposition provides robust financial market analysis by extracting principal drivers from asset correlation matrices. This statistical method reduces noise in time series data, yielding more reliable regime-dependent correlation assessments for portfolio construction.